Tootfinder

AMD bringt den achten Ryzen 5 5600
Sechskerner für die AM4-Plattform haben es AMD angetan. Neu im Portfolio: der Ryzen 5 5600F mit recht niedrigem Takt.
https://www.heise.de/news/AMD-bringt-den-a

FashionPose: Text to Pose to Relight Image Generation for Personalized Fashion Visualization
Chuancheng Shi, Yixiang Chen, Burong Lei, Jichao Chen
https://arxiv.org/abs/2507.13311

FashionPose: Text to Pose to Relight Image Generation for Personalized Fashion Visualization
Realistic and controllable garment visualization is critical for fashion e-commerce, where users expect personalized previews under diverse poses and lighting conditions. Existing methods often rely on predefined poses, limiting semantic flexibility and illumination adaptability. To address this, we introduce FashionPose, the first unified text-to-pose-to-relighting generation framework. Given a natural language description, our method first predicts a 2D human pose, then employs a diffusion mo…

Testing and benchmarking emerging supercomputers via the MFC flow solver
Benjamin Wilfong, Anand Radhakrishnan, Henry A. Le Berre, Tanush Prathi, Stephen Abbott, Spencer H. Bryngelson
https://arxiv.org/abs/2509.13575

Testing and benchmarking emerging supercomputers via the MFC flow solver
Deploying new supercomputers requires testing and evaluation via application codes. Portable, user-friendly tools enable evaluation, and the Multicomponent Flow Code (MFC), a computational fluid dynamics (CFD) code, addresses this need. MFC is adorned with a toolchain that automates input generation, compilation, batch job submission, regression testing, and benchmarking. The toolchain design enables users to evaluate compiler-hardware combinations for correctness and performance with limited s…

Early Detection of Branched Broomrape (Phelipanche ramosa) Infestation in Tomato Crops Using Leaf Spectral Analysis and Machine Learning
Mohammadreza Narimani, Alireza Pourreza, Ali Moghimi, Parastoo Farajpoor, Hamid Jafarbiglu, Mohsen B. Mesgaran
https://arxiv.org/abs/2509.12074

Early Detection of Branched Broomrape (Phelipanche ramosa) Infestation in Tomato Crops Using Leaf Spectral Analysis and Machine Learning
Branched broomrape (Phelipanche ramosa) is a chlorophyll-deficient parasitic weed that threatens tomato production by extracting nutrients from the host. We investigate early detection using leaf-level spectral reflectance (400-2500 nm) and ensemble machine learning. In a field experiment in Woodland, California, we tracked 300 tomato plants across growth stages defined by growing degree days (GDD). Leaf reflectance was acquired with a portable spectrometer and preprocessed (band denoising, 1 n…

Chemical transformation of CO in evolving protoplanetary discs across stellar masses: a route to C-rich inner regions
Andrew D. Sellek, Ewine F. van Dishoeck
https://arxiv.org/abs/2507.11631

Chemical transformation of CO in evolving protoplanetary discs across stellar masses: a route to C-rich inner regions
Protoplanetary discs around Very Low Mass Stars (VLMS) show hydrocarbon-rich MIR spectra indicative of C/O>1 in their inner discs, in contrast to discs around higher-mass hosts which mostly show O-bearing species. One scenario proposed to elevate C/O in VLMS inner discs is the advection of O-depleted gas from the outer disc. However, if CO gas remains abundant, C/O can be at most ~1. We test if chemical transformation of CO into other species allows this transport scenario to produce C/O signif…

PARROT: Portable Android Reproducible traffic Observation Tool
Andrea Jimenez-Berenguel, Celeste Campo, Marta Moure-Garrido, Carlos Garcia-Rubio, Daniel D\'iaz-Sanchez, Florina Almenares
https://arxiv.org/abs/2509.09537

PARROT: Portable Android Reproducible traffic Observation Tool
The rapid evolution of mobile security protocols and limited availability of current datasets constrains research in app traffic analysis. This paper presents PARROT, a reproducible and portable traffic capture system for systematic app traffic collection using Android Virtual Devices. The system provides automated environment setup, configurable Android versions, traffic recording management, and labeled captures extraction with human-in-the-loop app interaction. PARROT integrates mitmproxy fo…

Dug out a 1975 Burroughs leased line data set, an IBM PC Convertible, and a Morrow Decision Master system to bring back to Ireland.
I'm still trying to figure what to do with the Compaq Portable, TRS-80, Z89 disk drive, SGI Indigo², 7011 POWERstation RS6000 system, DEC PC, and (oh God) the monitors. And I'm pretty sure there are full Amiga 1000 and 2000 systems in there. Atari 1040STFM (2x). A full Burroughs financial system. Mainframe terminals. More C64s than any person eve…

Professional bakers often use old bread to mix it with in new sourdough to make really really good bread.
You can adapt this by adding coffee leftovers to the new water when brewing coffee. This makes coffee extraordinarily delicious - especially if the old coffee has ripened inside the can over the weekend.
#protip

BPD-Neo: An MRI Dataset for Lung-Trachea Segmentation with Clinical Data for Neonatal Bronchopulmonary Dysplasia
Rachit Saluja, Arzu Kovanlikaya, Candace Chien, Lauren Kathryn Blatt, Jeffrey M. Perlman, Stefan Worgall, Mert R. Sabuncu, Jonathan P. Dyke
https://arxiv.org/abs/2506.23305

BPD-Neo: An MRI Dataset for Lung-Trachea Segmentation with Clinical Data for Neonatal Bronchopulmonary Dysplasia
Bronchopulmonary dysplasia (BPD) is a common complication among preterm neonates, with portable X-ray imaging serving as the standard diagnostic modality in neonatal intensive care units (NICUs). However, lung magnetic resonance imaging (MRI) offers a non-invasive alternative that avoids sedation and radiation while providing detailed insights into the underlying mechanisms of BPD. Leveraging high-resolution 3D MRI data, advanced image processing and semantic segmentation algorithms can be deve…

Multi-agent Reinforcement Learning-based In-place Scaling Engine for Edge-cloud Systems
Jovan Prodanov, Bla\v{z} Bertalani\v{c}, Carolina Fortuna, Shih-Kai Chou, Matja\v{z} Branko Juri\v{c}, Ramon Sanchez-Iborra, Jernej Hribar
https://arxiv.org/abs/2507.07671

Multi-agent Reinforcement Learning-based In-place Scaling Engine for Edge-cloud Systems
Modern edge-cloud systems face challenges in efficiently scaling resources to handle dynamic and unpredictable workloads. Traditional scaling approaches typically rely on static thresholds and predefined rules, which are often inadequate for optimizing resource utilization and maintaining performance in distributed and dynamic environments. This inefficiency hinders the adaptability and performance required in edge-cloud infrastructures, which can only be achieved through the newly proposed in-…